Overview

Dataset statistics

Number of variables17
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory138.2 B

Variable types

Text1
Numeric16

Alerts

AT is highly overall correlated with BE and 14 other fieldsHigh correlation
BE is highly overall correlated with AT and 14 other fieldsHigh correlation
DE is highly overall correlated with AT and 14 other fieldsHigh correlation
DK is highly overall correlated with AT and 14 other fieldsHigh correlation
ES is highly overall correlated with AT and 14 other fieldsHigh correlation
FI is highly overall correlated with AT and 14 other fieldsHigh correlation
FR is highly overall correlated with AT and 14 other fieldsHigh correlation
GB is highly overall correlated with AT and 14 other fieldsHigh correlation
IE is highly overall correlated with AT and 14 other fieldsHigh correlation
IT is highly overall correlated with AT and 14 other fieldsHigh correlation
NL is highly overall correlated with AT and 14 other fieldsHigh correlation
NO is highly overall correlated with AT and 14 other fieldsHigh correlation
PL is highly overall correlated with AT and 14 other fieldsHigh correlation
PT is highly overall correlated with AT and 14 other fieldsHigh correlation
SE is highly overall correlated with AT and 14 other fieldsHigh correlation
Total general is highly overall correlated with AT and 14 other fieldsHigh correlation
Fecha has unique valuesUnique
DE has unique valuesUnique
DK has unique valuesUnique
ES has unique valuesUnique
FI has unique valuesUnique
FR has unique valuesUnique
GB has unique valuesUnique
IE has unique valuesUnique
NO has unique valuesUnique
SE has unique valuesUnique
IT has unique valuesUnique
PL has unique valuesUnique
NL has unique valuesUnique
BE has unique valuesUnique
PT has unique valuesUnique
AT has unique valuesUnique
Total general has unique valuesUnique

Reproduction

Analysis started2024-02-11 16:35:42.915986
Analysis finished2024-02-11 16:36:29.530945
Duration46.61 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Fecha
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-02-11T17:36:29.856022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.0983607
Min length7

Characters and Unicode

Total characters433
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row2019-01
2nd row2019-02
3rd row2019-03
4th row2019-04
5th row2019-05
ValueCountFrequency (%)
2019-01 1
 
1.6%
2020-04 1
 
1.6%
2019-03 1
 
1.6%
2019-04 1
 
1.6%
2019-05 1
 
1.6%
2019-06 1
 
1.6%
2019-07 1
 
1.6%
2019-08 1
 
1.6%
2019-09 1
 
1.6%
2019-10 1
 
1.6%
Other values (52) 52
83.9%
2024-02-11T17:36:30.520938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 130
30.0%
0 122
28.2%
- 60
13.9%
1 49
 
11.3%
9 17
 
3.9%
3 17
 
3.9%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (11) 18
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.1%
Dash Punctuation 60
 
13.9%
Lowercase Letter 11
 
2.5%
Uppercase Letter 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 130
36.1%
0 122
33.9%
1 49
 
13.6%
9 17
 
4.7%
3 17
 
4.7%
5 5
 
1.4%
6 5
 
1.4%
7 5
 
1.4%
4 5
 
1.4%
8 5
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
18.2%
l 2
18.2%
e 2
18.2%
o 1
9.1%
t 1
9.1%
g 1
9.1%
n 1
9.1%
r 1
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 421
97.2%
Latin 12
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 130
30.9%
0 122
29.0%
- 60
14.3%
1 49
 
11.6%
9 17
 
4.0%
3 17
 
4.0%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (2) 6
 
1.4%
Latin
ValueCountFrequency (%)
a 2
16.7%
l 2
16.7%
e 2
16.7%
T 1
8.3%
o 1
8.3%
t 1
8.3%
g 1
8.3%
n 1
8.3%
r 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 130
30.0%
0 122
28.2%
- 60
13.9%
1 49
 
11.3%
9 17
 
3.9%
3 17
 
3.9%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (11) 18
 
4.2%

DE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean948755.25
Minimum127221
Maximum28937035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:30.802319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127221
5-th percentile163410
Q1256330
median455736
Q3691096
95-th percentile802147
Maximum28937035
Range28809814
Interquartile range (IQR)434766

Descriptive statistics

Standard deviation3650437.6
Coefficient of variation (CV)3.8476072
Kurtosis60.497193
Mean948755.25
Median Absolute Deviation (MAD)225982
Skewness7.7626894
Sum57874070
Variance1.3325694 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:36:31.046119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
390095 1
 
1.6%
701574 1
 
1.6%
872577 1
 
1.6%
564756 1
 
1.6%
541456 1
 
1.6%
636850 1
 
1.6%
761050 1
 
1.6%
753073 1
 
1.6%
700125 1
 
1.6%
774010 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
127221 1
1.6%
142324 1
1.6%
159972 1
1.6%
163410 1
1.6%
170694 1
1.6%
172730 1
1.6%
178853 1
1.6%
181127 1
1.6%
181614 1
1.6%
183480 1
1.6%
ValueCountFrequency (%)
28937035 1
1.6%
888281 1
1.6%
872577 1
1.6%
802147 1
1.6%
787931 1
1.6%
779098 1
1.6%
774010 1
1.6%
761050 1
1.6%
757296 1
1.6%
757225 1
1.6%

DK
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean409489.57
Minimum21825
Maximum12489432
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:31.310168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21825
5-th percentile23939
Q1108476
median231732
Q3287247
95-th percentile423952
Maximum12489432
Range12467607
Interquartile range (IQR)178771

Descriptive statistics

Standard deviation1577196.2
Coefficient of variation (CV)3.8516151
Kurtosis60.232928
Mean409489.57
Median Absolute Deviation (MAD)83555
Skewness7.7377107
Sum24978864
Variance2.487548 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:36:31.536447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
252447 1
 
1.6%
230351 1
 
1.6%
224628 1
 
1.6%
198983 1
 
1.6%
184273 1
 
1.6%
280649 1
 
1.6%
231732 1
 
1.6%
251034 1
 
1.6%
332521 1
 
1.6%
381287 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
21825 1
1.6%
22740 1
1.6%
23628 1
1.6%
23939 1
1.6%
29986 1
1.6%
30606 1
1.6%
32575 1
1.6%
33887 1
1.6%
35460 1
1.6%
42256 1
1.6%
ValueCountFrequency (%)
12489432 1
1.6%
511444 1
1.6%
454807 1
1.6%
423952 1
1.6%
404556 1
1.6%
401073 1
1.6%
381287 1
1.6%
341268 1
1.6%
332521 1
1.6%
325546 1
1.6%

ES
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1226963.7
Minimum41313
Maximum37422393
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:31.698474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41313
5-th percentile103989
Q1217202
median651038
Q3982142
95-th percentile1441943
Maximum37422393
Range37381080
Interquartile range (IQR)764940

Descriptive statistics

Standard deviation4733592.7
Coefficient of variation (CV)3.8579728
Kurtosis59.816341
Mean1226963.7
Median Absolute Deviation (MAD)411931
Skewness7.6986611
Sum74844786
Variance2.2406899 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:36:31.874093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
248836 1
 
1.6%
651038 1
 
1.6%
917877 1
 
1.6%
934308 1
 
1.6%
719187 1
 
1.6%
1048341 1
 
1.6%
1198723 1
 
1.6%
1441943 1
 
1.6%
1562659 1
 
1.6%
1818309 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
41313 1
1.6%
87001 1
1.6%
103721 1
1.6%
103989 1
1.6%
111829 1
1.6%
115786 1
1.6%
128901 1
1.6%
137642 1
1.6%
141215 1
1.6%
142260 1
1.6%
ValueCountFrequency (%)
37422393 1
1.6%
1818309 1
1.6%
1562659 1
1.6%
1441943 1
1.6%
1424541 1
1.6%
1292539 1
1.6%
1265311 1
1.6%
1232868 1
1.6%
1198723 1
1.6%
1108167 1
1.6%

FI
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140736.03
Minimum9392
Maximum4292449
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:32.094329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9392
5-th percentile10826
Q129534
median75771
Q3103474
95-th percentile153018
Maximum4292449
Range4283057
Interquartile range (IQR)73940

Descriptive statistics

Standard deviation542214.33
Coefficient of variation (CV)3.8527044
Kurtosis60.161318
Mean140736.03
Median Absolute Deviation (MAD)31962
Skewness7.7309574
Sum8584898
Variance2.9399638 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:32.348252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90786 1
 
1.6%
44793 1
 
1.6%
89477 1
 
1.6%
81227 1
 
1.6%
63532 1
 
1.6%
75771 1
 
1.6%
96838 1
 
1.6%
107733 1
 
1.6%
94975 1
 
1.6%
111128 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
9392 1
1.6%
10590 1
1.6%
10748 1
1.6%
10826 1
1.6%
11480 1
1.6%
11691 1
1.6%
11809 1
1.6%
12398 1
1.6%
13313 1
1.6%
14048 1
1.6%
ValueCountFrequency (%)
4292449 1
1.6%
160609 1
1.6%
154092 1
1.6%
153018 1
1.6%
152975 1
1.6%
143054 1
1.6%
139804 1
1.6%
125330 1
1.6%
123569 1
1.6%
111359 1
1.6%

FR
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean580808.46
Minimum25684
Maximum17714658
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:32.602652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25684
5-th percentile55439
Q1145863
median305092
Q3414859
95-th percentile597700
Maximum17714658
Range17688974
Interquartile range (IQR)268996

Descriptive statistics

Standard deviation2236722
Coefficient of variation (CV)3.8510493
Kurtosis60.270126
Mean580808.46
Median Absolute Deviation (MAD)145463
Skewness7.7412792
Sum35429316
Variance5.0029253 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:36:32.829954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
271023 1
 
1.6%
450555 1
 
1.6%
451944 1
 
1.6%
361811 1
 
1.6%
257640 1
 
1.6%
332787 1
 
1.6%
473779 1
 
1.6%
546485 1
 
1.6%
597700 1
 
1.6%
741357 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
25684 1
1.6%
30178 1
1.6%
44456 1
1.6%
55439 1
1.6%
57578 1
1.6%
59171 1
1.6%
78843 1
1.6%
85541 1
1.6%
86305 1
1.6%
87254 1
1.6%
ValueCountFrequency (%)
17714658 1
1.6%
741357 1
1.6%
609280 1
1.6%
597700 1
1.6%
552564 1
1.6%
546485 1
1.6%
508435 1
1.6%
482852 1
1.6%
473779 1
1.6%
470630 1
1.6%

GB
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3291061.8
Minimum225582
Maximum1.0037738 Ɨ 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:33.053216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum225582
5-th percentile311662
Q11157720
median1650630
Q32309968
95-th percentile3472841
Maximum1.0037738 Ɨ 108
Range1.001518 Ɨ 108
Interquartile range (IQR)1152248

Descriptive statistics

Standard deviation12670768
Coefficient of variation (CV)3.8500548
Kurtosis60.335593
Mean3291061.8
Median Absolute Deviation (MAD)659338
Skewness7.7475333
Sum2.0075477 Ɨ 108
Variance1.6054837 Ɨ 1014
MonotonicityNot monotonic
2024-02-11T17:36:33.298766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1581704 1
 
1.6%
1920954 1
 
1.6%
1650630 1
 
1.6%
1254617 1
 
1.6%
931571 1
 
1.6%
1669968 1
 
1.6%
2064305 1
 
1.6%
2472261 1
 
1.6%
2699637 1
 
1.6%
4055347 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
225582 1
1.6%
228885 1
1.6%
295343 1
1.6%
311662 1
1.6%
400407 1
1.6%
402249 1
1.6%
420244 1
1.6%
421481 1
1.6%
433812 1
1.6%
545509 1
1.6%
ValueCountFrequency (%)
100377385 1
1.6%
4055347 1
1.6%
3651611 1
1.6%
3472841 1
1.6%
3182324 1
1.6%
3100401 1
1.6%
2922519 1
1.6%
2886671 1
1.6%
2788727 1
1.6%
2699637 1
1.6%

IE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192674.72
Minimum12667
Maximum5876579
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:33.510851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12667
5-th percentile16713
Q158258
median101825
Q3138023
95-th percentile181931
Maximum5876579
Range5863912
Interquartile range (IQR)79765

Descriptive statistics

Standard deviation741768.5
Coefficient of variation (CV)3.8498486
Kurtosis60.349258
Mean192674.72
Median Absolute Deviation (MAD)36294
Skewness7.748656
Sum11753158
Variance5.5022051 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:33.673561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79002 1
 
1.6%
98155 1
 
1.6%
86056 1
 
1.6%
82814 1
 
1.6%
78204 1
 
1.6%
118552 1
 
1.6%
136003 1
 
1.6%
175664 1
 
1.6%
175025 1
 
1.6%
188547 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
12667 1
1.6%
13099 1
1.6%
15476 1
1.6%
16713 1
1.6%
18860 1
1.6%
19787 1
1.6%
20292 1
1.6%
20483 1
1.6%
22415 1
1.6%
23351 1
1.6%
ValueCountFrequency (%)
5876579 1
1.6%
197690 1
1.6%
188547 1
1.6%
181931 1
1.6%
180310 1
1.6%
175664 1
1.6%
175025 1
1.6%
173917 1
1.6%
170425 1
1.6%
165868 1
1.6%

NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean236998.49
Minimum14832
Maximum7228454
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:34.028551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14832
5-th percentile18274
Q160542
median114313
Q3171250
95-th percentile259003
Maximum7228454
Range7213622
Interquartile range (IQR)110708

Descriptive statistics

Standard deviation913341.28
Coefficient of variation (CV)3.8537852
Kurtosis60.090318
Mean236998.49
Median Absolute Deviation (MAD)56937
Skewness7.7244298
Sum14456908
Variance8.341923 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:34.308030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110163 1
 
1.6%
101720 1
 
1.6%
120611 1
 
1.6%
136443 1
 
1.6%
127413 1
 
1.6%
158584 1
 
1.6%
160370 1
 
1.6%
187059 1
 
1.6%
251892 1
 
1.6%
327483 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
14832 1
1.6%
16358 1
1.6%
17134 1
1.6%
18274 1
1.6%
18656 1
1.6%
18824 1
1.6%
18897 1
1.6%
19176 1
1.6%
19187 1
1.6%
19197 1
1.6%
ValueCountFrequency (%)
7228454 1
1.6%
327483 1
1.6%
287149 1
1.6%
259003 1
1.6%
251892 1
1.6%
243841 1
1.6%
236732 1
1.6%
222249 1
1.6%
220478 1
1.6%
215612 1
1.6%

SE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean728333.8
Minimum30096
Maximum22214181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:34.532703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30096
5-th percentile65222
Q1180337
median352660
Q3530604
95-th percentile802020
Maximum22214181
Range22184085
Interquartile range (IQR)350267

Descriptive statistics

Standard deviation2807887.1
Coefficient of variation (CV)3.8552201
Kurtosis59.996221
Mean728333.8
Median Absolute Deviation (MAD)177944
Skewness7.715945
Sum44428362
Variance7.8842299 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:36:34.800316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
303539 1
 
1.6%
271819 1
 
1.6%
289877 1
 
1.6%
226632 1
 
1.6%
180337 1
 
1.6%
297926 1
 
1.6%
339562 1
 
1.6%
352660 1
 
1.6%
534997 1
 
1.6%
655042 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
30096 1
1.6%
39830 1
1.6%
62089 1
1.6%
65222 1
1.6%
65302 1
1.6%
66548 1
1.6%
68766 1
1.6%
72938 1
1.6%
75635 1
1.6%
83298 1
1.6%
ValueCountFrequency (%)
22214181 1
1.6%
1253485 1
1.6%
1059672 1
1.6%
802020 1
1.6%
710825 1
1.6%
671767 1
1.6%
655042 1
1.6%
652605 1
1.6%
642415 1
1.6%
630460 1
1.6%

IT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean781093.34
Minimum20899
Maximum23823347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:35.069113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20899
5-th percentile65080
Q1219213
median403565
Q3605395
95-th percentile885787
Maximum23823347
Range23802448
Interquartile range (IQR)386182

Descriptive statistics

Standard deviation3010153.9
Coefficient of variation (CV)3.8537698
Kurtosis60.091329
Mean781093.34
Median Absolute Deviation (MAD)201830
Skewness7.7245397
Sum47646694
Variance9.0610267 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:36:35.381962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338805 1
 
1.6%
344433 1
 
1.6%
553788 1
 
1.6%
499342 1
 
1.6%
408220 1
 
1.6%
465884 1
 
1.6%
694652 1
 
1.6%
810382 1
 
1.6%
927260 1
 
1.6%
1136764 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
20899 1
1.6%
43136 1
1.6%
63534 1
1.6%
65080 1
1.6%
71391 1
1.6%
72908 1
1.6%
74170 1
1.6%
77371 1
1.6%
77808 1
1.6%
78847 1
1.6%
ValueCountFrequency (%)
23823347 1
1.6%
1136764 1
1.6%
927260 1
1.6%
885787 1
1.6%
810382 1
1.6%
726734 1
1.6%
694652 1
1.6%
689942 1
1.6%
671035 1
1.6%
662193 1
1.6%

PL
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean216629.8
Minimum5922
Maximum6607209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:35.626676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5922
5-th percentile23426
Q155072
median87366
Q3192316
95-th percentile242647
Maximum6607209
Range6601287
Interquartile range (IQR)137244

Descriptive statistics

Standard deviation835222.52
Coefficient of variation (CV)3.8555291
Kurtosis59.976004
Mean216629.8
Median Absolute Deviation (MAD)61530
Skewness7.7136657
Sum13214418
Variance6.9759665 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:35.855676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
117179 1
 
1.6%
87366 1
 
1.6%
102377 1
 
1.6%
93344 1
 
1.6%
80000 1
 
1.6%
96095 1
 
1.6%
100584 1
 
1.6%
149603 1
 
1.6%
178211 1
 
1.6%
212206 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
5922 1
1.6%
8680 1
1.6%
22207 1
1.6%
23426 1
1.6%
24805 1
1.6%
24902 1
1.6%
25298 1
1.6%
25836 1
1.6%
29857 1
1.6%
31585 1
1.6%
ValueCountFrequency (%)
6607209 1
1.6%
253417 1
1.6%
247780 1
1.6%
242647 1
1.6%
236356 1
1.6%
226727 1
1.6%
218979 1
1.6%
217223 1
1.6%
212206 1
1.6%
210548 1
1.6%

NL
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean233700.85
Minimum10996
Maximum7127876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:36.138116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10996
5-th percentile30111
Q178702
median115654
Q3159380
95-th percentile230133
Maximum7127876
Range7116880
Interquartile range (IQR)80678

Descriptive statistics

Standard deviation899353.63
Coefficient of variation (CV)3.8483113
Kurtosis60.450646
Mean233700.85
Median Absolute Deviation (MAD)43055
Skewness7.7583552
Sum14255752
Variance8.0883696 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:36.453707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95141 1
 
1.6%
112184 1
 
1.6%
101643 1
 
1.6%
105920 1
 
1.6%
101816 1
 
1.6%
120089 1
 
1.6%
134716 1
 
1.6%
159380 1
 
1.6%
156512 1
 
1.6%
151615 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
10996 1
1.6%
16452 1
1.6%
26171 1
1.6%
30111 1
1.6%
30337 1
1.6%
32666 1
1.6%
38097 1
1.6%
44521 1
1.6%
52155 1
1.6%
54030 1
1.6%
ValueCountFrequency (%)
7127876 1
1.6%
256131 1
1.6%
235825 1
1.6%
230133 1
1.6%
216554 1
1.6%
210322 1
1.6%
199905 1
1.6%
199637 1
1.6%
197204 1
1.6%
196481 1
1.6%

BE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean182511.74
Minimum17090
Maximum5566608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:36.745404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17090
5-th percentile24074
Q171660
median104570
Q3120858
95-th percentile141229
Maximum5566608
Range5549518
Interquartile range (IQR)49198

Descriptive statistics

Standard deviation701809.19
Coefficient of variation (CV)3.8452825
Kurtosis60.65117
Mean182511.74
Median Absolute Deviation (MAD)21479
Skewness7.7771724
Sum11133216
Variance4.9253614 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:37.057999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75992 1
 
1.6%
122227 1
 
1.6%
129203 1
 
1.6%
103599 1
 
1.6%
90876 1
 
1.6%
103931 1
 
1.6%
113995 1
 
1.6%
115798 1
 
1.6%
133976 1
 
1.6%
145276 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
17090 1
1.6%
22473 1
1.6%
23044 1
1.6%
24074 1
1.6%
28037 1
1.6%
29088 1
1.6%
30607 1
1.6%
31336 1
1.6%
36978 1
1.6%
47232 1
1.6%
ValueCountFrequency (%)
5566608 1
1.6%
151494 1
1.6%
145276 1
1.6%
141229 1
1.6%
139171 1
1.6%
137521 1
1.6%
133976 1
1.6%
129915 1
1.6%
129203 1
1.6%
128019 1
1.6%

PT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189019.08
Minimum6512
Maximum5765082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:37.342916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6512
5-th percentile14229
Q151660
median93110
Q3151306
95-th percentile201253
Maximum5765082
Range5758570
Interquartile range (IQR)99646

Descriptive statistics

Standard deviation728339.31
Coefficient of variation (CV)3.8532581
Kurtosis60.124952
Mean189019.08
Median Absolute Deviation (MAD)56767
Skewness7.7275183
Sum11530164
Variance5.3047814 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:37.595776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36251 1
 
1.6%
151810 1
 
1.6%
143322 1
 
1.6%
147632 1
 
1.6%
132526 1
 
1.6%
164844 1
 
1.6%
148317 1
 
1.6%
156414 1
 
1.6%
167448 1
 
1.6%
201253 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
6512 1
1.6%
8154 1
1.6%
10348 1
1.6%
14229 1
1.6%
14707 1
1.6%
17979 1
1.6%
18784 1
1.6%
21058 1
1.6%
21585 1
1.6%
22260 1
1.6%
ValueCountFrequency (%)
5765082 1
1.6%
212007 1
1.6%
205955 1
1.6%
201253 1
1.6%
192389 1
1.6%
188344 1
1.6%
172574 1
1.6%
167448 1
1.6%
167165 1
1.6%
164844 1
1.6%

AT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91905.902
Minimum5146
Maximum2803130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:37.769137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5146
5-th percentile10248
Q124122
median51191
Q373456
95-th percentile91428
Maximum2803130
Range2797984
Interquartile range (IQR)49334

Descriptive statistics

Standard deviation354076.82
Coefficient of variation (CV)3.8526016
Kurtosis60.168045
Mean91905.902
Median Absolute Deviation (MAD)25421
Skewness7.7316028
Sum5606260
Variance1.253704 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:36:37.935158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30666 1
 
1.6%
54406 1
 
1.6%
70581 1
 
1.6%
68332 1
 
1.6%
75242 1
 
1.6%
78415 1
 
1.6%
77641 1
 
1.6%
84293 1
 
1.6%
76612 1
 
1.6%
84709 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
5146 1
1.6%
6633 1
1.6%
8458 1
1.6%
10248 1
1.6%
10282 1
1.6%
10392 1
1.6%
10398 1
1.6%
11232 1
1.6%
12007 1
1.6%
13933 1
1.6%
ValueCountFrequency (%)
2803130 1
1.6%
101871 1
1.6%
99143 1
1.6%
91428 1
1.6%
91371 1
1.6%
88174 1
1.6%
84709 1
1.6%
84293 1
1.6%
78415 1
1.6%
77641 1
1.6%

Total general
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9450682.6
Minimum783912
Maximum2.8824582 Ɨ 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:36:38.115919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum783912
5-th percentile918673
Q12842346
median5343385
Q36506618
95-th percentile9138445
Maximum2.8824582 Ɨ 108
Range2.8746191 Ɨ 108
Interquartile range (IQR)3664272

Descriptive statistics

Standard deviation36374497
Coefficient of variation (CV)3.8488751
Kurtosis60.413453
Mean9450682.6
Median Absolute Deviation (MAD)1405248
Skewness7.7547756
Sum5.7649164 Ɨ 108
Variance1.323104 Ɨ 1015
MonotonicityNot monotonic
2024-02-11T17:36:38.368669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4021629 1
 
1.6%
5343385 1
 
1.6%
5804591 1
 
1.6%
4859760 1
 
1.6%
3972293 1
 
1.6%
5648686 1
 
1.6%
6732267 1
 
1.6%
7763782 1
 
1.6%
8589550 1
 
1.6%
10984333 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
783912 1
1.6%
871060 1
1.6%
878289 1
1.6%
918673 1
1.6%
1050149 1
1.6%
1101925 1
1.6%
1172354 1
1.6%
1186911 1
1.6%
1191848 1
1.6%
1343928 1
1.6%
ValueCountFrequency (%)
288245818 1
1.6%
10984333 1
1.6%
9817224 1
1.6%
9138445 1
1.6%
8589550 1
1.6%
8275417 1
1.6%
7763782 1
1.6%
7527069 1
1.6%
7142771 1
1.6%
7013632 1
1.6%

Interactions

2024-02-11T17:36:26.717842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:43.795533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:46.638552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:50.102068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:53.662306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:56.445945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:00.407138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:03.709961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:06.807184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:09.341654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:11.565459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:13.661674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:16.833257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:19.289840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:21.887239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:24.211023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:26.885939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:43.975517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:46.841802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:50.250695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:53.860961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:56.786419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:00.594211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:03.928001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:06.911983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:09.551279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:11.687885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:13.804514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:16.977004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:19.453463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:22.067335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:24.313824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:27.050587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:44.168635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:47.038200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:50.449720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:54.089595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:57.105926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:00.739748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:04.154288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:07.088499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:09.704885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:11.822905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:14.075830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:17.110793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:19.640507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:22.225710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:24.483233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:27.224988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:44.399784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:47.270912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:50.678156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:54.268276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-02-11T17:36:19.141481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:21.724850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:24.053927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:36:26.585703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-02-11T17:36:38.559024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ATBEDEDKESFIFRGBIEITNLNOPLPTSETotal general
AT1.0000.6590.8110.8860.9490.8550.8410.5220.6800.9140.8250.8850.8880.8910.7850.870
BE0.6591.0000.7990.6710.7500.6680.8700.8050.7730.7970.7800.7410.7440.8110.7250.846
DE0.8110.7991.0000.7550.8520.7340.9370.6090.6590.8630.7500.7750.8360.8600.6790.844
DK0.8860.6710.7551.0000.8800.9150.8150.6510.7790.8820.8370.9150.9170.7970.9050.905
ES0.9490.7500.8520.8801.0000.8600.9150.6050.7610.9560.8430.9020.8960.9110.8120.927
FI0.8550.6680.7340.9150.8601.0000.7830.7040.8030.8750.8050.9090.8920.7450.8930.902
FR0.8410.8700.9370.8150.9150.7831.0000.7040.7850.9330.7970.8390.8510.9050.7600.924
GB0.5220.8050.6090.6510.6050.7040.7041.0000.9030.6760.6120.7260.5970.5690.6970.795
IE0.6800.7730.6590.7790.7610.8030.7850.9031.0000.8080.7370.8280.7040.6900.8020.871
IT0.9140.7970.8630.8820.9560.8750.9330.6760.8081.0000.8730.9430.9170.9120.8620.962
NL0.8250.7800.7500.8370.8430.8050.7970.6120.7370.8731.0000.8560.9120.8510.8800.883
NO0.8850.7410.7750.9150.9020.9090.8390.7260.8280.9430.8561.0000.9110.8440.9030.951
PL0.8880.7440.8360.9170.8960.8920.8510.5970.7040.9170.9120.9111.0000.8650.9040.918
PT0.8910.8110.8600.7970.9110.7450.9050.5690.6900.9120.8510.8440.8651.0000.7620.872
SE0.7850.7250.6790.9050.8120.8930.7600.6970.8020.8620.8800.9030.9040.7621.0000.902
Total general0.8700.8460.8440.9050.9270.9020.9240.7950.8710.9620.8830.9510.9180.8720.9021.000

Missing values

2024-02-11T17:36:29.079732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-11T17:36:29.408817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

FechaDEDKESFIFRGBIENOSEITPLNLBEPTATTotal general
02019-0139009525244724883690786271023158170479002110163303539338805117179951417599236251306664021629
12019-0237206226299924914790023201188173717510561610563533295723036075012589095112436343295873938137
22019-03405078287247290156101802263866202299714545212890139278129765063045827886794355194327674637667
32019-04376287243601299507665682527022226281165868114855339539304156626991075129094157970292904737776
42019-054147912144243177565601830297128866711704251143133790613569046664813085510718671095294915618609
52019-064013911811173091885814030509227887271819311376913541584599927013713812111195963782289385590364
62019-074057802428213625647392935974731823241739171089244307064377949192513471713752162861286636234193
72019-083818042127673522418312734782129225191412471088354099552810636888810779312604961133249615630203
82019-093635291768932783717155822460320942111090351134093756932941376360510621211766954027245124467464
92019-103351651269102815435907715779914328129806892861388791264250560261012299577254524241223568949
FechaDEDKESFIFRGBIENOSEITPLNLBEPTATTotal general
512023-047879312703967915561040984148592375027127397220478671767614072247780186017122573151306575147142771
522023-05779098246819693194879924706301910028115576174678580150662193210548180736128019163687549566458304
532023-06757225253181864193830394603551425899117862141863512557624420196518199637119744192389562776005159
542023-076255293255461232868942704683701741708138910207822610408671035208238256131151494212007692967013632
552023-0868171830716310720901011034327921641263126132165808546761597546206394230133129915205955914286536201
562023-0965274826616411026751398043981321311398119185145249507581591130192316235825105614172574913716031766
572023-10539068315287126531111135940235211577201254921569208020206899422267272103221050171671651018716376573
582023-1144991945480710837601034743180001291356101825287149125348560650521722319648190748137180991436691055
592023-124431135114441057806102997303186134390182607236732105967256867125341721655497015141329881746506618
60Total general28937035124894323742239342924491771465810037738558765797228454222141812382334766072097127876556660857650822803130288245818